NMF offers several advantages over other techniques like Principal Component Analysis (PCA) or Independent Component Analysis (ICA):
Interpretability: The non-negativity constraint results in a parts-based, sparse representation, making the results more interpretable and align with the physical reality of toxicological data. Handling Missing Data: NMF is more robust to missing data, a common issue in toxicological datasets. Dimensionality Reduction: It effectively reduces the dimensionality of complex datasets, allowing for the identification of key patterns without extensive preprocessing.
